docstr: Test that slices can be created by indexing into a term, and that they
  have the correct shape when used as inputs.
docstr_tok: ["Test","that","slices","can","be","created","by","indexing","into","a","term",",","and","that","they","have","the","correct","shape","when","used","as","inputs","."]
code: def test_slice(self, my_asset_column, window_length_):
      """
      Test that slices can be created by indexing into a term, and that they
      have the correct shape when used as inputs.
      """
      sids = self.sids
      my_asset = self.asset_finder.retrieve_asset(
          self.sids[my_asset_column]
      )
  
      returns = Returns(window_length=2, inputs=[self.col])
      returns_slice = returns[my_asset]
  
      class UsesSlicedInput(CustomFactor):
          window_length = window_length_
          inputs = [returns, returns_slice]
  
          def compute(self, today, assets, out, returns, returns_slice):
              # Make sure that our slice is the correct shape (i.e. has only
              # one column) and that it has the same values as the original
              # returns factor from which it is derived.
              assert returns_slice.shape == (self.window_length, 1)
              assert returns.shape == (self.window_length, len(sids))
              check_arrays(
                  returns_slice[:, 0], returns[:, my_asset_column]
              )
  
      # Assertions about the expected slice data are made in the `compute`
      # function of our custom factor above.
      self.run_pipeline(
          Pipeline(columns={"uses_sliced_input": UsesSlicedInput()}),
          self.pipeline_start_date,
          self.pipeline_end_date,
      )
  
imports: from numpy import where
  from pandas import Int64Index, Timestamp
  from pandas.util.testing import assert_frame_equal
  from zipline.assets import Asset, ExchangeInfo
  from zipline.errors import NonExistentAssetInTimeFrame, NonSliceableTerm, NonWindowSafeInput, UnsupportedPipelineOutput
  from zipline.pipeline import CustomFactor, Factor, Filter, Classifier, Pipeline
  from zipline.pipeline.data import USEquityPricing
  from zipline.pipeline.data.testing import TestingDataSet
  from zipline.pipeline.domain import US_EQUITIES
  from zipline.pipeline.factors import Returns, RollingLinearRegressionOfReturns, RollingPearsonOfReturns, RollingSpearmanOfReturns, SimpleMovingAverage
  from zipline.testing import AssetID, AssetIDPlusDay, check_arrays, OpenPrice, parameter_space
  from zipline.testing.fixtures import WithSeededRandomPipelineEngine, ZiplineTestCase
  from zipline.utils.numpy_utils import datetime64ns_dtype
label_desc: Use image node_id 2 for calling the SliceTestCase obj's underlying member method code with example usage: obj.test_slice(my_asset_column, window_length_) without return types